The deregulation of the telecommunications industry has resulted in an environment where subscribers are given many choices of telecommunications service providers. Each service provider typically offers different rate plans that govern the cost the subscriber pays for various voice and data transmissions. In addition, the network over which the telecommunication services are provided, may be only partially owned or leased by the subscriber's particular service provider. To keep track of subscriber billing or network usage and communication services, service providers rely upon records created for each subscriber transaction on the network. For example, a call detail record (CDR) is generated when a telephone call is placed by a subscriber across the network. Groups of CDRs are stored in files of various formats and sizes for retrieval and processing by a computer-based billing system. To be automatically processed, however, each CDR must be properly formatted.
For example, call detail records are created when subscribers use an automated attendant system such as the InterVoice Brite Interactive Voice Response (IVR) system. The automated attendant system creates billing records which are forwarded to downstream processing systems which verify service provider billing for network time or create customer billing records for network usage. In a typical busy hour such systems can create files containing approximately 5,000 CDRs. On occasion, software errors or configuration issues can result in the creation of CDRs which contain errors and cause processing problems for the downstream billing and processing systems. In the case of automated attendant systems, the first analysis point for each file downstream of the automated attendant system is a system known as “splitter.” The splitter system divides the CDRs, typically by service provider or network vendor, and further forwards each record to the appropriate subsystem. If a CDR contains any one of several conditions or errors, the entire file is rejected by the splitter system. To date, the only method for processing files containing records with errors is to manually search the file for the malformed record and edit the file to correct or delete the offending record. Obviously, in files containing thousands of records, this off-line error detection and correction method can be very time consuming, expensive, and labor intensive. Accordingly, there is a need for an improved and automated CDR error detection and correction system and method.